Article(id=1320882779529785665, tenantId=1146029695717560320, journalId=1260987677001138203, issueId=1320880138208784845, articleNumber=null, orderNo=null, doi=10.13386/j.issn1002-0306.2025080093, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1754841600000, receivedDateStr=2025-08-11, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1792852595455, onlineDateStr=2026-10-24, pubDate=1785513600000, pubDateStr=2026-08-01, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792852595455, onlineIssueDateStr=2026-10-24, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792852595455, creator=13701087609, updateTime=1792852595455, updator=13701087609, issue=Issue{id=1320880138208784845, tenantId=1146029695717560320, journalId=1260987677001138203, year='2026', volume='47', issue='15', pageStart='1', pageEnd='524', issueExtLink='null', onlineDate='null', pubDate='1785513600000', pubDateStr='2026-08-01', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792851965715, creator='13701087609', updateTime=1792851965715, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=356, endPage=364, ext={EN=ArticleExt(id=1320882779785638210, articleId=1320882779529785665, tenantId=1146029695717560320, journalId=1260987677001138203, language=EN, title=Analysis and Comprehensive Evaluation of Processing Quality Characteristics of Wheat Varieties in Henan Province, columnId=1261343843585241413, journalTitle=Science and Technology of Food Industry, columnName=Analysis and Determination, runingTitle=null, highlight=null, articleAbstract=

In order to effectively evaluate the quality differences among different wheat varieties, 18 varieties cultivated in the Henan region were selected as the research subjects. An analysis was conducted on their grain, flour, and dough quality characteristics. Furthermore, a comprehensive evaluation model was established by integrating correlation analysis and principal component analysis. Cluster analysis was used to classify 18 different wheat varieties, analyzing the characteristics and potential application value of each category. The results showed that the bulk density had the smallest coefficient of variation (1.89%), while the formation time had the largest (78.96%). One variety (Xinmai 26) met the quality standards for strong-gluten wheat in all six key indicators, and seven varieties met the standards for medium-strong gluten. Various quality traits exhibited different degrees of correlation, with the strongest correlation observed between development time and stability time (0.982). Principal component analysis simplified the 14 evaluation indicators into four principal components, with a cumulative contribution rate of 82.005%. Weighted scores based on these components identified the top three varieties with the best comprehensive quality: Xinmai 26, Luohan 22, and Yumai 49, indicating high value for targeted breeding and processing. Cluster analysis categorized the varieties into three groups: Group Ⅰ (10 varieties) exhibited moderate grain quality but the poorest flour and dough quality; Group Ⅱ (6 varieties) had poorer grain quality but moderate flour and dough quality, suggesting inferior milling but acceptable processing quality; Group Ⅲ (2 varieties) demonstrated the best grain and flour quality, along with good dough quality, indicating superior overall milling, processing, and end-use potential. This study provides a theoretical reference for selecting and promoting high-quality wheat varieties and for the development of the processing industry.

, authors=Bing HONG1, Tingting HU1, Haoran GONG1, *, Xiaofang GAO1, Miaoran SU1, Min LI1, Jie XIE2, *, authorsList=Bing HONG, Tingting HU, Haoran GONG, Xiaofang GAO, Miaoran SU, Min LI, Jie XIE, authorCompany=null, correspAuthors=Haoran GONG, Jie XIE, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright © 2026 Science and Technology of Food Industry. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1320882782323192136, articleId=1320882779529785665, tenantId=1146029695717560320, journalId=1260987677001138203, language=CN, title=河南小麦品种加工品质特性分析与综合评价, columnId=1261343846139572559, journalTitle=食品工业科技, columnName=分析检测, runingTitle=null, highlight=null, articleAbstract=

为有效评价不同品种小麦品质的差异,以河南地区种植的18个不同小麦品种为研究对象,对其籽粒、面粉及面团品质特性进行分析,并结合相关性分析和主成分分析方法建立一套综合评价模型。通过聚类分析对18个不同小麦品种进行分类,分析每类特点挖掘潜在应用价值。结果表明,小麦容重的变异系数最小(1.89%),形成时间的变异系数最大(78.96%)。其中有1个品种(新麦26)6项指标达到我国小麦品种品质分类标准强筋品质要求,7个品种达到中强筋品质要求。各品质性状间呈现不同程度的相关性,形成时间与面团稳定时间相关性最强(0.982)。通过主成分分析将14个评价指标简化为4个主成分,累计贡献率为82.005%,并对14个指标分别赋予权重得到综合品质前三的品种为新麦26、洛旱22、豫麦49,极具定向培育及开发加工价值。通过聚类分析将小麦分为三类:第Ⅰ类籽粒品质居中,面粉品质和面团品质最差,聚集了10个小麦品种;第Ⅱ类籽粒品质较差,面粉品质和面团品质居中,表明其磨粉品质较差,加工品质较好,聚集了6个小麦品种;第Ⅲ类聚集了2个小麦品种,籽粒品质和面粉品质最好,面团品质较好,表明其磨粉、加工品质及食用品质均较好。本研究结果为优质小麦品种的筛选、推广种植及加工产业发展提供了理论参考。

, authors=洪冰1, 胡婷婷1, 弓浩然1, *, 高晓芳1, 苏淼冉1, 李敏1, 谢婕2, *, authorsList=洪冰, 胡婷婷, 弓浩然, 高晓芳, 苏淼冉, 李敏, 谢婕, authorCompany=null, correspAuthors=弓浩然, 谢婕, authorNote=

洪冰(1989−),女,硕士,工程师,研究方向:食品安全与质量控制,E-mail:

, correspAuthorsNote=
弓浩然(1992−),男,硕士,助理工程师,研究方向:粮油检测,E-mail:。
谢婕(1988−),女,硕士,农艺师,研究方向:农产品加工,E-mail:。
, copyrightStatement=版权所有 © 2026《食品工业科技》编辑部, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=aIl+sppaVHgQvu/W/aB+8w==, magXml=TphH+h/qDBU4I9ydwbMVTA==, pdfUrl=null, pdf=FJbqQJjvPzmwZhSpqZQAfQ==, pdfFileSize=1430213, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=BySV8+ZXZyyXAMrnmk66Nw==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=jVhjcnAU1Rc9B+DsHC3gfg==, mapNumber=null, fund=null)}, authors=[Author(id=1320882782927171920, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=hongbingice@163.com, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1320882783250133330, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, authorId=1320882782927171920, language=EN, stringName=Bing HONG, firstName=Bing, middleName=null, lastName=HONG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1Zhengzhou Product Quality Inspection and Testing Center, Zhengzhou 450000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1320882783334019411, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, authorId=1320882782927171920, language=CN, stringName=洪冰, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1郑州市产品质量检验检测中心,河南郑州 450000, bio={"content":"

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Tai'an: Shandong Agricultural University, 2024., articleTitle=null, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1320882782558073161, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, xref=1, ext=[AuthorCompanyExt(id=1320882782566461770, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, companyId=1320882782558073161, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1Zhengzhou Product Quality Inspection and Testing Center, Zhengzhou 450000, China), AuthorCompanyExt(id=1320882782570656075, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, companyId=1320882782558073161, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1郑州市产品质量检验检测中心,河南郑州 450000)]), AuthorCompany(id=1320882782826508620, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, xref=2, ext=[AuthorCompanyExt(id=1320882782834897229, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, companyId=1320882782826508620, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2Luoyang Academy of Agricultural and Forestry Sciences, Luoyang 471000, China), AuthorCompanyExt(id=1320882782839091534, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, companyId=1320882782826508620, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2洛阳市农林科学院,河南洛阳 471000)])], figs=[ArticleFig(id=1320882787800953212, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, language=EN, label=Fig.1, caption=Correlation analysis of wheat quality indices, figureFileSmall=GssEPavQTedLqMUsaf9FsQ==, figureFileBig=BySV8+ZXZyyXAMrnmk66Nw==, tableContent=null), ArticleFig(id=1320882787868062077, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, language=CN, label=图1, caption=小麦品质指标相关性分析

注:*:P<0.05;**:P<0.01;红色表示2个指标之间呈现出正相关关系,蓝色表示2个指标之间呈现出负相关关系,颜色越深表示相关程度越高,其R2越接近1。

, figureFileSmall=GssEPavQTedLqMUsaf9FsQ==, figureFileBig=BySV8+ZXZyyXAMrnmk66Nw==, tableContent=null), ArticleFig(id=1320882788086165886, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, language=EN, label=Fig.2, caption=Cluster analysis based on phenotypic characters, figureFileSmall=vH61HAYQNIAocDnTmDwSgw==, figureFileBig=K+IkzU0KzsaHrbRRPXKkTw==, tableContent=null), ArticleFig(id=1320882788170051967, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, language=CN, label=图2, caption=基于表型数据的聚类分析图, figureFileSmall=vH61HAYQNIAocDnTmDwSgw==, figureFileBig=K+IkzU0KzsaHrbRRPXKkTw==, tableContent=null), ArticleFig(id=1320882788249743744, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, language=EN, label=Table 1, caption=

Wheat cultivars used in this experiment

, figureFileSmall=null, figureFileBig=null, tableContent=
品种序号品种品种序号品种
1矮抗5810新麦26
2百农30711豫农211
3百农419912豫农982
4存麦1113郑麦188
5洛旱2214郑麦369
6平麦18915众麦1号
7伟隆16916周麦22
8温麦16817周麦27
9豫麦4918周麦30
), ArticleFig(id=1320882788337824129, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, language=CN, label=表1, caption=

实验所用小麦品种

, figureFileSmall=null, figureFileBig=null, tableContent=
品种序号品种品种序号品种
1矮抗5810新麦26
2百农30711豫农211
3百农419912豫农982
4存麦1113郑麦188
5洛旱2214郑麦369
6平麦18915众麦1号
7伟隆16916周麦22
8温麦16817周麦27
9豫麦4918周麦30
), ArticleFig(id=1320882788421710210, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, language=EN, label=Table 2, caption=

Quality characteristics of grain and flour from different wheat varieties

, figureFileSmall=null, figureFileBig=null, tableContent=
品种序号籽粒品质面粉品质
容重(g/L)千粒重(g)灰分(%)硬度指数(%)蛋白质含量
(以干基计)(%)
湿面筋含量(%)沉淀指数(mL)面筋指数(%)
1810.33±1.15a41.47±0.15i1.61±0.02c64.17±0.35d14.30±0.20ef30.47±0.15h27.00±0.50h68.67±0.58h
2794.67±0.58d41.70±0.10hi1.48±0.01ef63.47±0.25e13.90±0.40ghij27.53±0.21l38.33±0.29d72.33±0.58f
3796.33±0.58cd42.40±0.10g1.49±0.02e65.33±0.51c14.73±0.06cd33.47±0.21b35.67±0.29e82.00±0.00cd
4785.00±1.00e43.07±0.06f1.51±0.02d59.27±0.21h15.07±0.06c30.90±0.20fg31.17±0.58g85.00±1.00b
5754.67±1.53j41.57±0.12i1.62±0.01bc64.03±0.21d14.13±0.12efgh31.60±0.10e43.17±0.76b76.33±0.58e
6802.67±0.58b45.70±0.10a1.34±0.01j57.20±0.26i14.20±0.10efg31.17±0.15f35.83±0.29e69.00±1.73h
7810.33±0.58a45.67±0.06a1.48±0.01ef63.03±0.21e13.53±0.12jk28.33±0.06k41.83±0.76c81.67±0.58d
8770.00±1.00h41.47±0.06i1.47±0.00f63.07±0.25e13.30±0.17k26.27±0.12m31.67±0.76g70.67±0.58g
9782.33±1.53f41.93±0.15h1.69±0.01a67.03±0.32a16.67±0.15a33.20±0.10c30.83±0.76g87.00±1.00a
10803.67±1.53b45.23±0.06b1.68±0.01a66.30±0.20b15.47±0.29b31.60±0.10e46.33±0.29a83.33±0.58c
11768.33±0.58i40.20±0.26j1.47±0.01ef64.17±0.15d14.87±0.35c32.23±0.21d35.17±0.29e59.33±0.58j
12794.67±0.58d43.10±0.26f1.62±0.01bc63.23±0.15e14.43±0.29de30.87±0.21g31.50±0.87g57.00±0.00k
13778.00±1.00g44.23±0.21d1.64±0.02b62.00±0.26f13.73±0.21ij29.50±0.10i32.83±0.29f58.67±0.58j
14786.00±0.00e43.07±0.15f1.38±0.01i63.10±0.10e13.97±0.21fghi31.10±0.26fg35.00±0.87e62.67±0.58i
15784.33±0.58e44.77±0.06c1.38±0.02i59.40±0.17h13.80±0.17hij30.53±0.06h30.83±0.29g42.67±1.53n
16796.67±1.15c44.93±0.15c1.41±0.01h64.13±0.06d14.73±0.12cd32.33±0.21d31.83±0.76g58.00±1.00jk
17785.67±1.15e43.90±0.17e1.44±0.01g61.23±0.21g13.23±0.06k28.67±0.06j30.83±0.29g54.67±1.53l
18779.33±0.58g44.03±0.21de1.39±0.01i59.23±0.15h14.10±0.26efghi36.77±0.12a42.17±0.76c46.33±1.53m
最小值754.6740.201.3457.2013.2326.2727.0042.67
最大值810.3345.701.6967.0316.6736.7746.3387.00
平均值787.9443.251.5162.7414.3430.9235.1167.52
标准差14.861.650.112.610.842.405.2813.42
变异系数CV(%)1.893.827.374.165.847.7615.0419.87
), ArticleFig(id=1320882788513984899, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, language=CN, label=表2, caption=

不同品种小麦的籽粒品质和面粉品质特性

, figureFileSmall=null, figureFileBig=null, tableContent=
品种序号籽粒品质面粉品质
容重(g/L)千粒重(g)灰分(%)硬度指数(%)蛋白质含量
(以干基计)(%)
湿面筋含量(%)沉淀指数(mL)面筋指数(%)
1810.33±1.15a41.47±0.15i1.61±0.02c64.17±0.35d14.30±0.20ef30.47±0.15h27.00±0.50h68.67±0.58h
2794.67±0.58d41.70±0.10hi1.48±0.01ef63.47±0.25e13.90±0.40ghij27.53±0.21l38.33±0.29d72.33±0.58f
3796.33±0.58cd42.40±0.10g1.49±0.02e65.33±0.51c14.73±0.06cd33.47±0.21b35.67±0.29e82.00±0.00cd
4785.00±1.00e43.07±0.06f1.51±0.02d59.27±0.21h15.07±0.06c30.90±0.20fg31.17±0.58g85.00±1.00b
5754.67±1.53j41.57±0.12i1.62±0.01bc64.03±0.21d14.13±0.12efgh31.60±0.10e43.17±0.76b76.33±0.58e
6802.67±0.58b45.70±0.10a1.34±0.01j57.20±0.26i14.20±0.10efg31.17±0.15f35.83±0.29e69.00±1.73h
7810.33±0.58a45.67±0.06a1.48±0.01ef63.03±0.21e13.53±0.12jk28.33±0.06k41.83±0.76c81.67±0.58d
8770.00±1.00h41.47±0.06i1.47±0.00f63.07±0.25e13.30±0.17k26.27±0.12m31.67±0.76g70.67±0.58g
9782.33±1.53f41.93±0.15h1.69±0.01a67.03±0.32a16.67±0.15a33.20±0.10c30.83±0.76g87.00±1.00a
10803.67±1.53b45.23±0.06b1.68±0.01a66.30±0.20b15.47±0.29b31.60±0.10e46.33±0.29a83.33±0.58c
11768.33±0.58i40.20±0.26j1.47±0.01ef64.17±0.15d14.87±0.35c32.23±0.21d35.17±0.29e59.33±0.58j
12794.67±0.58d43.10±0.26f1.62±0.01bc63.23±0.15e14.43±0.29de30.87±0.21g31.50±0.87g57.00±0.00k
13778.00±1.00g44.23±0.21d1.64±0.02b62.00±0.26f13.73±0.21ij29.50±0.10i32.83±0.29f58.67±0.58j
14786.00±0.00e43.07±0.15f1.38±0.01i63.10±0.10e13.97±0.21fghi31.10±0.26fg35.00±0.87e62.67±0.58i
15784.33±0.58e44.77±0.06c1.38±0.02i59.40±0.17h13.80±0.17hij30.53±0.06h30.83±0.29g42.67±1.53n
16796.67±1.15c44.93±0.15c1.41±0.01h64.13±0.06d14.73±0.12cd32.33±0.21d31.83±0.76g58.00±1.00jk
17785.67±1.15e43.90±0.17e1.44±0.01g61.23±0.21g13.23±0.06k28.67±0.06j30.83±0.29g54.67±1.53l
18779.33±0.58g44.03±0.21de1.39±0.01i59.23±0.15h14.10±0.26efghi36.77±0.12a42.17±0.76c46.33±1.53m
最小值754.6740.201.3457.2013.2326.2727.0042.67
最大值810.3345.701.6967.0316.6736.7746.3387.00
平均值787.9443.251.5162.7414.3430.9235.1167.52
标准差14.861.650.112.610.842.405.2813.42
变异系数CV(%)1.893.827.374.165.847.7615.0419.87
), ArticleFig(id=1320882788614648196, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, language=EN, label=Table 3, caption=

Quality characteristics of dough from different wheat varieties

, figureFileSmall=null, figureFileBig=null, tableContent=
品种序号粉质特性拉伸特性
形成时间(min)面团稳定时间(min)粉质质量指数(mm)最大拉伸阻力(BU)50 mm拉伸阻力(BU)延伸性(mm)拉伸面积(cm2)
13.23±0.06i4.20±0.10j85.67±1.15h214.67±3.21n175.67±3.06o157.00±1.00d41.67±0.58l
26.47±0.15e8.57±0.06e52.67±1.15l264.33±2.31j237.00±2.65j161.33±1.53bc54.33±0.58i
35.77±0.15f8.90±0.10d239.33±2.31b396.00±3.00f336.00±1.73e132.67±0.58hi81.33±1.53c
43.27±0.06i3.57±0.06k109.00±1.00f347.67±1.15h267.67±1.15h141.67±2.52f66.67±1.15f
513.60±0.10b16.90±0.20b309.67±1.53a411.67±1.53d292.00±3.00g126.00±2.65j77.33±1.15d
61.87±0.06k4.37±0.12ij97.33±0.58g259.00±2.00k160.00±1.73q163.33±2.52b57.67±1.15h
710.20±0.17c13.07±0.12c198.33±1.53d279.67±3.06i251.33±1.53i137.33±3.06g67.33±1.15f
83.53±0.06h4.83±0.12h68.67±0.58i235.67±2.08l203.67±2.52n154.67±3.79de43.67±0.58k
98.93±0.15d12.97±0.21c53.67±1.15l794.67±5.03a667.67±6.03a135.33±3.06gh49.67±1.53j
1015.87±0.12a21.40±0.10a203.33±1.53c662.00±4.58b530.00±4.00b156.00±1.73d141.67±1.53a
111.57±0.12l1.77±0.12l56.67±0.58k259.67±2.52k208.67±1.53m158.00±1.00cd53.67±0.58i
123.63±0.12h5.47±0.06f61.67±0.58j222.67±1.53m165.67±0.58p189.67±2.52a62.00±1.00g
134.97±0.12g8.97±0.15d147.00±1.73e497.33±3.06c345.00±1.00d138.67±1.15fg88.67±0.58b
141.83±0.12k4.33±0.15ij55.67±0.58k410.33±2.52e360.67±1.15c125.00±2.00j71.00±1.00e
151.97±0.06k1.67±0.06l28.33±0.58m97.67±1.53o95.67±1.15r158.67±3.06cd20.67±0.58m
163.10±0.10i3.77±0.06k53.00±1.00l268.33±1.15j218.33±2.52l159.00±3.61cd52.67±1.53i
172.73±0.12j5.20±0.17g57.67±1.15k257.67±2.31k227.33±1.15k151.67±2.08e43.00±1.00kl
183.07±0.12i4.53±0.06i61.67±0.58j381.67±2.08g331.33±0.58f131.00±1.00i81.67±1.53c
最小值1.571.6728.3397.6795.67125.0020.67
最大值15.8721.40309.67794.67667.67189.67141.67
平均值5.317.47107.74347.82281.87144.3170.82
标准差4.195.4279.12168.46137.6322.9935.31
变异系数CV(%)78.9672.5973.4448.4348.8315.9349.86
), ArticleFig(id=1320882788711117189, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, language=CN, label=表3, caption=

不同品种小麦的面团品质特性

, figureFileSmall=null, figureFileBig=null, tableContent=
品种序号粉质特性拉伸特性
形成时间(min)面团稳定时间(min)粉质质量指数(mm)最大拉伸阻力(BU)50 mm拉伸阻力(BU)延伸性(mm)拉伸面积(cm2)
13.23±0.06i4.20±0.10j85.67±1.15h214.67±3.21n175.67±3.06o157.00±1.00d41.67±0.58l
26.47±0.15e8.57±0.06e52.67±1.15l264.33±2.31j237.00±2.65j161.33±1.53bc54.33±0.58i
35.77±0.15f8.90±0.10d239.33±2.31b396.00±3.00f336.00±1.73e132.67±0.58hi81.33±1.53c
43.27±0.06i3.57±0.06k109.00±1.00f347.67±1.15h267.67±1.15h141.67±2.52f66.67±1.15f
513.60±0.10b16.90±0.20b309.67±1.53a411.67±1.53d292.00±3.00g126.00±2.65j77.33±1.15d
61.87±0.06k4.37±0.12ij97.33±0.58g259.00±2.00k160.00±1.73q163.33±2.52b57.67±1.15h
710.20±0.17c13.07±0.12c198.33±1.53d279.67±3.06i251.33±1.53i137.33±3.06g67.33±1.15f
83.53±0.06h4.83±0.12h68.67±0.58i235.67±2.08l203.67±2.52n154.67±3.79de43.67±0.58k
98.93±0.15d12.97±0.21c53.67±1.15l794.67±5.03a667.67±6.03a135.33±3.06gh49.67±1.53j
1015.87±0.12a21.40±0.10a203.33±1.53c662.00±4.58b530.00±4.00b156.00±1.73d141.67±1.53a
111.57±0.12l1.77±0.12l56.67±0.58k259.67±2.52k208.67±1.53m158.00±1.00cd53.67±0.58i
123.63±0.12h5.47±0.06f61.67±0.58j222.67±1.53m165.67±0.58p189.67±2.52a62.00±1.00g
134.97±0.12g8.97±0.15d147.00±1.73e497.33±3.06c345.00±1.00d138.67±1.15fg88.67±0.58b
141.83±0.12k4.33±0.15ij55.67±0.58k410.33±2.52e360.67±1.15c125.00±2.00j71.00±1.00e
151.97±0.06k1.67±0.06l28.33±0.58m97.67±1.53o95.67±1.15r158.67±3.06cd20.67±0.58m
163.10±0.10i3.77±0.06k53.00±1.00l268.33±1.15j218.33±2.52l159.00±3.61cd52.67±1.53i
172.73±0.12j5.20±0.17g57.67±1.15k257.67±2.31k227.33±1.15k151.67±2.08e43.00±1.00kl
183.07±0.12i4.53±0.06i61.67±0.58j381.67±2.08g331.33±0.58f131.00±1.00i81.67±1.53c
最小值1.571.6728.3397.6795.67125.0020.67
最大值15.8721.40309.67794.67667.67189.67141.67
平均值5.317.47107.74347.82281.87144.3170.82
标准差4.195.4279.12168.46137.6322.9935.31
变异系数CV(%)78.9672.5973.4448.4348.8315.9349.86
), ArticleFig(id=1320882788790808966, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, language=EN, label=Table 4, caption=

Principal component loading matrix, eigenvalues and contribution rates

, figureFileSmall=null, figureFileBig=null, tableContent=
品质指标主成分因子(PC)
主成分1主成分2主成分3主成分4
千粒重X1−0.0280.6280.3030.506
灰分X20.703−0.366−0.3550.217
硬度指数X30.651−0.456−0.310−0.037
蛋白质含量X40.571−0.5990.3440.240
湿面筋含量X50.251−0.1180.833−0.015
沉淀指数X60.5840.6620.113−0.006
面筋指数X70.703−0.129−0.306−0.156
形成时间X80.8880.250−0.2660.095
面团稳定时间X90.9170.243−0.2230.114
粉质质量指数X100.6750.465−0.237−0.269
最大拉伸阻力X110.865−0.2490.2930.039
50 mm拉伸阻力X120.839−0.2900.310−0.001
延伸性X13−0.443−0.164−0.3550.746
拉伸面积X140.7540.3650.1760.206
特征值6.4432.2071.7491.081
方差贡献率(%)46.01915.76712.4947.725
累积贡献率(%)46.01961.78674.28082.005
), ArticleFig(id=1320882788874695047, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, language=CN, label=表4, caption=

主成分载荷矩阵、特征值及贡献率

, figureFileSmall=null, figureFileBig=null, tableContent=
品质指标主成分因子(PC)
主成分1主成分2主成分3主成分4
千粒重X1−0.0280.6280.3030.506
灰分X20.703−0.366−0.3550.217
硬度指数X30.651−0.456−0.310−0.037
蛋白质含量X40.571−0.5990.3440.240
湿面筋含量X50.251−0.1180.833−0.015
沉淀指数X60.5840.6620.113−0.006
面筋指数X70.703−0.129−0.306−0.156
形成时间X80.8880.250−0.2660.095
面团稳定时间X90.9170.243−0.2230.114
粉质质量指数X100.6750.465−0.237−0.269
最大拉伸阻力X110.865−0.2490.2930.039
50 mm拉伸阻力X120.839−0.2900.310−0.001
延伸性X13−0.443−0.164−0.3550.746
拉伸面积X140.7540.3650.1760.206
特征值6.4432.2071.7491.081
方差贡献率(%)46.01915.76712.4947.725
累积贡献率(%)46.01961.78674.28082.005
), ArticleFig(id=1320882788987941256, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, language=EN, label=Table 5, caption=

Principal component scores and composite scores of wheat

, figureFileSmall=null, figureFileBig=null, tableContent=
品种序号F1F2F3F4FF排名
1−1.28−1.79−1.26−0.24−1.2815
2−0.59−0.03−1.660−0.5910
31.9−0.030.39−1.330.994
4−0.31−0.570.45−0.37−0.259
53.461.48−1.16−1.641.892
6−2.151.60.950.88−0.6711
71.272.56−1.27−0.290.985
8−1.74−0.4−2.07−0.76−1.4417
94.13−3.871.080.081.753
106.071.23−0.042.163.841
11−1.34−1.630.21−0.48−1.0814
12−1.44−0.9−0.992.12−0.9313
130.820.48−0.130.170.556
14−0.49−0.041.28−1.27−0.218
15−4.010.570.40.54−2.0318
16−1.46−0.380.820.89−0.6812
17−2.290.4−0.46−0.04−1.2816
18−0.561.343.46−0.40.437
), ArticleFig(id=1320882789071827337, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, language=CN, label=表5, caption=

小麦主成分得分及综合得分

, figureFileSmall=null, figureFileBig=null, tableContent=
品种序号F1F2F3F4FF排名
1−1.28−1.79−1.26−0.24−1.2815
2−0.59−0.03−1.660−0.5910
31.9−0.030.39−1.330.994
4−0.31−0.570.45−0.37−0.259
53.461.48−1.16−1.641.892
6−2.151.60.950.88−0.6711
71.272.56−1.27−0.290.985
8−1.74−0.4−2.07−0.76−1.4417
94.13−3.871.080.081.753
106.071.23−0.042.163.841
11−1.34−1.630.21−0.48−1.0814
12−1.44−0.9−0.992.12−0.9313
130.820.48−0.130.170.556
14−0.49−0.041.28−1.27−0.218
15−4.010.570.40.54−2.0318
16−1.46−0.380.820.89−0.6812
17−2.290.4−0.46−0.04−1.2816
18−0.561.343.46−0.40.437
), ArticleFig(id=1320882789164102026, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, language=EN, label=Table 6, caption=

Average of 14 quality parameters in different groups

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品质参数类群
ⅠⅡⅢ
千粒重(g)43.30±1.98a43.07±0.98a43.60±2.26a
灰分(%)1.47±0.09b1.51±0.11b1.69±0.01a
硬度指数(%)62.10±2.38b62.00±2.53b66.50±0.71a
蛋白质含量(%)14.02±0.58b14.28±0.52b16.10±0.85a
湿面筋含量(%)29.84±2.03a32.23±2.58a32.40±1.13a
沉淀指数(mL)33.60±4.25a36.67±4.84a38.50±10.61a
面筋指数(%)63.50±11.14b68.50±15.08ab85.00±2.83a
形成时间(min)3.83±2.63b5.43±4.25b12.40±4.95a
面团稳定时间(min)5.31±3.36b7.87±5.02b17.20±5.94a
粉质质量指数(mm)76.10±46.81a153.83±101.69a128.50±105.36a
最大拉伸阻力(BU)236.10±52.69c407.50±49.72b728.50±94.05a
50 mm拉伸阻力(BU)194.40±45.89c322.17±35.05b599.00±97.58a
延伸性(mm)159.10±13.06a132.67±6.83b145.50±14.85ab
拉伸面积(cm2)49.80±13.03b77.83±7.96ab96.00±65.05a
), ArticleFig(id=1320882789264765323, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320882779529785665, language=CN, label=表6, caption=

不同类群14个品质参数平均数

, figureFileSmall=null, figureFileBig=null, tableContent=
品质参数类群
ⅠⅡⅢ
千粒重(g)43.30±1.98a43.07±0.98a43.60±2.26a
灰分(%)1.47±0.09b1.51±0.11b1.69±0.01a
硬度指数(%)62.10±2.38b62.00±2.53b66.50±0.71a
蛋白质含量(%)14.02±0.58b14.28±0.52b16.10±0.85a
湿面筋含量(%)29.84±2.03a32.23±2.58a32.40±1.13a
沉淀指数(mL)33.60±4.25a36.67±4.84a38.50±10.61a
面筋指数(%)63.50±11.14b68.50±15.08ab85.00±2.83a
形成时间(min)3.83±2.63b5.43±4.25b12.40±4.95a
面团稳定时间(min)5.31±3.36b7.87±5.02b17.20±5.94a
粉质质量指数(mm)76.10±46.81a153.83±101.69a128.50±105.36a
最大拉伸阻力(BU)236.10±52.69c407.50±49.72b728.50±94.05a
50 mm拉伸阻力(BU)194.40±45.89c322.17±35.05b599.00±97.58a
延伸性(mm)159.10±13.06a132.67±6.83b145.50±14.85ab
拉伸面积(cm2)49.80±13.03b77.83±7.96ab96.00±65.05a
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河南小麦品种加工品质特性分析与综合评价
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洪冰 1 , 胡婷婷 1 , 弓浩然 1, * , 高晓芳 1 , 苏淼冉 1 , 李敏 1 , 谢婕 2, *
食品工业科技 | 分析检测 2026,47(15): 356-364
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食品工业科技 |分析检测 2026 , 47 (15) : 356 -364
河南小麦品种加工品质特性分析与综合评价
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洪冰1 , 胡婷婷1, 弓浩然1, * , 高晓芳1, 苏淼冉1, 李敏1, 谢婕2, *
作者信息
  • 1郑州市产品质量检验检测中心,河南郑州 450000
  • 2洛阳市农林科学院,河南洛阳 471000
通讯作者:
弓浩然(1992−),男,硕士,助理工程师,研究方向:粮油检测,E-mail:。
谢婕(1988−),女,硕士,农艺师,研究方向:农产品加工,E-mail:。
作者简介:

洪冰(1989−),女,硕士,工程师,研究方向:食品安全与质量控制,E-mail:

Analysis and Comprehensive Evaluation of Processing Quality Characteristics of Wheat Varieties in Henan Province
Bing HONG1 , Tingting HU1, Haoran GONG1, * , Xiaofang GAO1, Miaoran SU1, Min LI1, Jie XIE2, *
Affiliations
  • 1Zhengzhou Product Quality Inspection and Testing Center, Zhengzhou 450000, China
  • 2Luoyang Academy of Agricultural and Forestry Sciences, Luoyang 471000, China
出版时间: 2026-08-01 doi: 10.13386/j.issn1002-0306.2025080093
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为有效评价不同品种小麦品质的差异,以河南地区种植的18个不同小麦品种为研究对象,对其籽粒、面粉及面团品质特性进行分析,并结合相关性分析和主成分分析方法建立一套综合评价模型。通过聚类分析对18个不同小麦品种进行分类,分析每类特点挖掘潜在应用价值。结果表明,小麦容重的变异系数最小(1.89%),形成时间的变异系数最大(78.96%)。其中有1个品种(新麦26)6项指标达到我国小麦品种品质分类标准强筋品质要求,7个品种达到中强筋品质要求。各品质性状间呈现不同程度的相关性,形成时间与面团稳定时间相关性最强(0.982)。通过主成分分析将14个评价指标简化为4个主成分,累计贡献率为82.005%,并对14个指标分别赋予权重得到综合品质前三的品种为新麦26、洛旱22、豫麦49,极具定向培育及开发加工价值。通过聚类分析将小麦分为三类:第Ⅰ类籽粒品质居中,面粉品质和面团品质最差,聚集了10个小麦品种;第Ⅱ类籽粒品质较差,面粉品质和面团品质居中,表明其磨粉品质较差,加工品质较好,聚集了6个小麦品种;第Ⅲ类聚集了2个小麦品种,籽粒品质和面粉品质最好,面团品质较好,表明其磨粉、加工品质及食用品质均较好。本研究结果为优质小麦品种的筛选、推广种植及加工产业发展提供了理论参考。

小麦  /  加工品质  /  主成分分析  /  聚类分析  /  综合评价

In order to effectively evaluate the quality differences among different wheat varieties, 18 varieties cultivated in the Henan region were selected as the research subjects. An analysis was conducted on their grain, flour, and dough quality characteristics. Furthermore, a comprehensive evaluation model was established by integrating correlation analysis and principal component analysis. Cluster analysis was used to classify 18 different wheat varieties, analyzing the characteristics and potential application value of each category. The results showed that the bulk density had the smallest coefficient of variation (1.89%), while the formation time had the largest (78.96%). One variety (Xinmai 26) met the quality standards for strong-gluten wheat in all six key indicators, and seven varieties met the standards for medium-strong gluten. Various quality traits exhibited different degrees of correlation, with the strongest correlation observed between development time and stability time (0.982). Principal component analysis simplified the 14 evaluation indicators into four principal components, with a cumulative contribution rate of 82.005%. Weighted scores based on these components identified the top three varieties with the best comprehensive quality: Xinmai 26, Luohan 22, and Yumai 49, indicating high value for targeted breeding and processing. Cluster analysis categorized the varieties into three groups: Group Ⅰ (10 varieties) exhibited moderate grain quality but the poorest flour and dough quality; Group Ⅱ (6 varieties) had poorer grain quality but moderate flour and dough quality, suggesting inferior milling but acceptable processing quality; Group Ⅲ (2 varieties) demonstrated the best grain and flour quality, along with good dough quality, indicating superior overall milling, processing, and end-use potential. This study provides a theoretical reference for selecting and promoting high-quality wheat varieties and for the development of the processing industry.

wheat  /  processing quality  /  principal component analysis  /  cluster analysis  /  comprehensive evaluation
洪冰, 胡婷婷, 弓浩然, 高晓芳, 苏淼冉, 李敏, 谢婕. 河南小麦品种加工品质特性分析与综合评价. 食品工业科技, 2026 , 47 (15) : 356 -364 . DOI: 10.13386/j.issn1002-0306.2025080093
Bing HONG, Tingting HU, Haoran GONG, Xiaofang GAO, Miaoran SU, Min LI, Jie XIE. Analysis and Comprehensive Evaluation of Processing Quality Characteristics of Wheat Varieties in Henan Province[J]. Science and Technology of Food Industry, 2026 , 47 (15) : 356 -364 . DOI: 10.13386/j.issn1002-0306.2025080093
小麦是禾本科小麦属,一年生或越年生草本植物,分布范围广,是我国北方地区重要的口粮作物,是河南省主要粮食经济作物之一[1]。我国小麦育种以提高产量和改良抗病性为主,且在长期演化和育种过程中形成了丰富的种质资源[2],因受基因型和环境等因素影响,不同小麦品种在品质特性上存在差异,且缺乏加工品质过硬的优质小麦品种[3]。目前小麦已经从“吃饱的需要”向“吃好的保障”发展[4],如何在提高产量的同时,改良小麦籽粒及小麦粉品质、筛选优质小麦,实现不同小麦品种籽粒或面粉的最终用途专用化成为我国小麦加工产业发展的主要方向。
品质(营养品质、加工品质、食用品质等)是小麦育种和生产的重要参考指标,也是影响产业竞争力的重要因素。小麦加工品质主要分为磨粉品质和食品加工品质。这两个方面分别对应小麦的初次加工和二次加工,对最终食用品质有着重要影响[5]。磨粉品质以籽粒容重、硬度指数为主要评价指标[3];食品加工品质以面粉的湿面筋含量、面筋指数、沉淀指数、面团流变学特性为主要评价指标;研究发现,蛋白质品质和籽粒硬度是制约中国小麦加工品质的主要因素[3],面粉及面团品质直接影响面包、馒头、糕点和面条等食品的加工品质[6−8]。目前,评价小麦及小麦粉的食用品质最准确的方法是直接进行面包烘焙、蒸制馒头、制成面条及糕点试验。但因试验过程较为复杂,耗时、费样,试验要求控制的条件严格,人为因素也较多。因此,常以与小麦、小麦粉食用品质密切相关的理化性状测定及面团特性试验(蛋白质含量、面筋指数、粉质特性、拉伸特性等),客观地反映小麦及小麦粉的品质,定量地评价小麦及小麦粉的品质和用途[9−10]。因此,对小麦加工品质进行进一步详细研究尤为重要。
近年来,以主成分分析和聚类分析为主的统计方法,通过将多个指标整合为新的综合指标,无需人为地为特征分配权重或创建理想值,能够更客观地反映性状之间的关系,因而在大麦[11]、茄子[12]、核桃[13]等多种经济作物的表型性状分析与评价中得到了广泛应用。周文菊等[14]通过主成分分析将18个指标转化为4个相互独立的综合指标,并筛选出青麦1号等优良品种。徐澜等[15]结合主成分分析对14个引种春麦进行综合评价,筛选出稳产性好,适合忻定盆地春播及相似生态区种植的品种。韩雪等[16]以UPGMA(不加权成对算数平均法)法对小麦遗传相似系数进行聚类分析,将200个小麦品种(系)分为5类,聚类分析结果与品种系谱关系基本一致。昝香存等[17]调查了607份小麦种质的13个品质性状,聚类分析结果将小麦种质分为6类,且不同类群间品质性状存在一定差异,各类群均具有其独特的特征。因此,采用主成分分析和聚类分析等方法可以从多个维度对种质性状进行评价,有助于更全面地了解小麦籽粒、面粉以及面团的质量[18]。
综合得出,小麦加工品质特性是多个品质指标相互作用的综合结果,直接决定其加工应用[19]。目前针对小麦品质的研究,主要侧重于育种及品质性状遗传组成分析,品种区域代表性不强,且对其籽粒、面粉及面团品质特性等综合品质缺乏系统研究[3,20−21]。因此,本研究以18个河南小麦品种为研究对象,分析了与小麦籽粒、面粉及面团相关的15个品质特性,运用相关分析、聚类分析、主成分分析等方法对小麦进行综合评价,可为河南地区优质小麦品种的筛选和加工产业发展提供理论基础和参考依据。
实验所选小麦均为郑州市粮食科学研究所2023~2024年收获的大田种植小麦,籽粒收获、风干存放2个月后进行测定。小麦品种详见表1;十二烷基硫酸钠(超纯级) 上海阿拉丁生化科技股份有限公司;乳酸(分析纯)、硼酸(分析纯)、硫酸(分析纯) 天津市科密欧化学试剂有限公司;氯化钠(分析纯) 国药集团化学试剂有限公司。
3100锤式实验室粉碎机、GM2200面筋数量及质量测定仪 瑞典波通仪器公司;LM-85/40实验磨 无锡穗邦科技有限公司;HGT-1000容重器 上海东方衡器有限公司;BF51828C-1高温炉 美国热电仪器公司;JYDB 100×40小麦硬度仪 布勒机械有限公司;8400型凯氏定氮仪 丹麦FOSS公司;Farinograph-E粉质仪、EXTENSOGRAPH-E拉伸仪 德国Brabender公司。
容重参照GB/T 5498-2013测定;千粒重参照GB/T 5519-2018测定;灰分参照GB 5009.4-2016第一法 食品中总灰分的测定,采用全麦粉进行灰分的测定;硬度指数参照GB/T 21304-2007测定;蛋白质参照GB 5009.5-2025第一法 凯氏定氮法测定,采用全麦粉进行蛋白质含量的测定;湿面筋参照GB/T 5506.2-2024小麦和小麦粉 面筋含量 第2部分:仪器法测定湿面筋和面筋指数,采用全麦粉加入氯化钠溶液制成面团,用GM2200面筋数量及质量测定仪清洗面团,使面筋分离出来;沉淀指数参照GB/T 15685-2011测定;面筋指数参照LS/T 6102-1995测定;粉质特性参照GB/T 14614-2019测定;拉伸特性参照GB/T 14615-2019测定。
所有指标的测定均取3个平行样,进行3次重复测定。Excel 2007进行标准差和变异系数计算;SPSS 27进行单因素分析、主成分分析及聚类分析,显著水平为P<0.05,Origin 2021进行相关性分析。
不同小麦品种特性指标测定结果见表2和表3。结果发现,在18种不同小麦品种中,15个品质性状存在不同程度的变异。15个品质特性的变异系数范围为1.89%~78.96%。4个籽粒指标的平均变异系数为4.31%,其中灰分变异系数最大(7.37%),平均值为1.51%;其次是硬度指数(4.16%)和千粒重(3.82%),平均值分别为62.74%和43.25 g;容重(1.89%)变异系数最小,平均值为787.94 g/L。4个面粉指标的平均变异系数为12.13%,其中面筋指数(19.87%)变异系数最大,平均值为67.52%;其次是沉淀指数(15.04%)和湿面筋含量(7.76%),平均值分别为35.11 mL和30.92%;蛋白质含量(5.84%)变异系数最小,平均值为14.34%。7个面团指标的平均变异系数为55.43%,其中形成时间(78.96%)变异系数最大,平均值为5.31 min;其次是粉质质量指数(73.44%)和面团稳定时间(72.59%),平均值分别为107.74 mm和7.47 min;延伸性(15.93%)变异系数最小,平均值为144.31 mm。在15个品质特性指标中,变异系数表现为形成时间>粉质质量指数>面团稳定时间>拉伸面积>50 mm拉伸阻力>最大拉伸阻力>面筋指数>延伸性>沉淀指数>湿面筋含量>灰分>蛋白质含量>硬度指数>千粒重>容重。韩雪等[18]发现小麦容重的变异系数最小,稳定时间的变异系数最大,而且面粉品质和面团品质变异系数大于籽粒品质变异系数。
分析可以看出,15个品质特性指标中,形成时间(78.96%)变异系数最大,范围为1.57~15.87 min,其次是粉质质量指数(73.44%)、面团稳定时间(72.59%),范围分别为28.33~309.67 mm、1.67~21.40 min,变异系数前三的品质性状均为小麦粉质特性,说明小麦粉质特性具有很大的改进潜力及丰富的遗传特性。容重、千粒重、硬度指数变异系数分别为1.89%、3.82%、4.16%,遗传特性相对稳定。各品质性状间呈现不同程度的相关性,其中面团品质改善的潜力更大,籽粒品质更稳定,这与李晓丽等[5]研究结果基本一致。
据GB/T 17320-2013《小麦品种品质分类》对小麦品种进行分类,硬度指数、蛋白质含量、湿面筋含量、稳定时间、最大拉伸阻力和拉伸面积6项指标全部达到强筋品质要求的有1个,即新麦26;达到中强筋品质要求的有7个,即百农4199、存麦11、洛旱22、伟隆169、郑麦188、郑麦369和周麦30。
大量研究表明[22−24],相关性分析可以直观地反映小麦品质特性之间的关系。对小麦不同品质指标之间的相关性进行分析,从图1可以看出,15个品质特性之间存在不同程度的相关性,且多数指标间存在显著(P<0.05)或极显著(P<0.01)相关性。
小麦籽粒容重与千粒重呈正相关(P<0.05),但小麦籽粒容重、千粒重与面粉指标和面团指标无显著相关性,表明容重、千粒重与面粉指标和面团指标之间的相关性相对独立;灰分与硬度指数、蛋白质含量、面筋指数及大部分面团品质特性呈显著(P<0.05)或极显著(P<0.01)正相关,与SHARIATIPOUR 等[25]、孙创举[26]研究一致;在面团指标方面,硬度指数与形成时间、面团稳定时间、最大拉伸阻力及50 mm拉伸阻力呈显著正相关(P<0.05),与陈妍妍等[27]研究一致。蛋白质含量与湿面筋含量、面筋指数呈显著正相关(P<0.05),与最大拉伸阻力、50 mm拉伸阻力呈极显著正相关(P<0.01),与韩雪等[16]研究一致。沉淀指数与粉质特性、拉伸面积呈极显著正相关(P<0.01)。面筋指数与形成时间、面团稳定时间呈极显著正相关(P<0.01),与粉质质量指数、最大拉伸阻力、50 mm拉伸阻力等面团特性呈显著正相关(P<0.05),表明面粉的面筋指数与面包筋力和面粉耐搅拌性呈正比,与姜小苓等[28]、王伟玲等[29]研究结果一致。然而,湿面筋含量与稳定时间、延伸性、拉伸面积等面团指标相关性不显著,与前人结果不一致[30−31]。进一步分析表明,小麦面筋蛋白主要由麦谷蛋白和麦醇溶蛋白组成,它们通过二硫键、氢键、离子键和疏水相互作用形成复杂的网络结构,使面团具有黏着性、湿润性、弹性等流变学特性[32−34]。然而,由于面筋蛋白的复杂结构,面团中其他成分的相互作用等原因,湿面筋含量通常无法准确反映面团流变学特性[35]。与湿面筋含量相比,面筋指数是保留在筛板上面筋重量与全部面筋重量的百分率,能更好地反映面筋筋力强弱。粉质特性指标与拉伸特性指标之间大多存在显著(P<0.05)或极显著(P<0.01)相关,其中形成时间与面团稳定时间相关性最强(0.982),与湿面筋含量、蛋白质含量与沉淀指数相关性较弱。虽然其他品质指标间也存在不同程度的相关性,但均未达到显著水平。因此,一个性状是否可以根据其与其他性状的相关性程度来间接改善,还需要进一步详细研究。
分析结果显示,不同品质指标间均存在相关性,导致部分信息重叠。因此,可进一步引入主成分分析以探寻评价河南小麦综合品质的主要特性指标。
主成分分析将多个指标简化为少数几个综合指标,根据主成分因子得分和方差贡献率计算综合得分。然而,使用这种方法没有综合考虑多个指标之间的相互作用和影响,可能导致信息丢失。因此,通过方差分析和相关性分析,将因素的单边影响和因素的相互影响相结合,对小麦进行品质分析,减少单一方法的局限性,增强结果可靠性。虽然15项品质指标间均存在不同程度的相关性,但容重与千粒重之外的指标间相关性均未达到显著水平,综合看其相关性最低,不适合被提取为公因子,为提高整体的相关性,取得更理想的降维结果,故在主成分分析中选择剔除容重指标。
为了避免不同维度对分析结果的影响,使用SPSS 27对14个品质指标的原始数据进行标准化处理,然后进行主成分分析,提取了特征值大于1的F1、F2、F3、F4共4个主成分因子(表4),特征值分别为6.443、2.207、1.749、1.081,其累计贡献率为82.005%,表明4个主成分因子代表了14个品质指标的大部分信息。第1主成分的贡献率为46.019%,主要由面团稳定时间、形成时间、最大拉伸阻力、50 mm拉伸阻力、拉伸面积、灰分、面筋指数、粉质质量指数、硬度指数构成;第2主成分的贡献率为15.767%,主要由沉淀指数、千粒重、蛋白质含量构成;第3主成分的贡献率为12.494%,主要由湿面筋含量构成;第4主成分的贡献率为7.725%,主要由延伸性构成;由此看出,这4个主要成分可以替代原始14个特征中的大部分信息,因此它们被用来代表原始的14个指标,可在小麦加工品质综合评价中使用。
根据表4构建得分模型,F1~F4表示不同小麦品种各主成分的得分公式,F为综合评价得分公式,得分及排名结果见表5。
F1=−0.011X1+0.277X2+0.256X3+0.225X4+0.099X5+0.230X6+0.277X7+0.350X8+0.361X9+0.266X10+0.341X11+0.330X12−0.174X13+0.297X14
F2=0.423X1−0.246X2−0.307X3−0.403X4−0.080X5+0.446X6−0.087X7+0.168X8+0.163X9+0.313X10−0.168X11−0.195X12−0.111X13+0.246X14
F3=0.229X1−0.268X2−0.234X3+0.260X4+0.630X5+0.086X6−0.231X7−0.201X8−0.169X9−0.179X10+0.222X11+0.235X12−0.268X13+0.133X14
F4=0.487X1+0.209X2−0.036X3+0.231X4−0.015X5−0.005X6−0.150X7+0.091X8+0.110X9−0.259X10+0.037X11−0.001X12+0.717X13+0.198X14
结合主成分因子得分公式,以方差贡献率占比为权重,小麦品质综合评价模型为:
F=0.561 F1+0.192F2+0.152F3+0.094F4
由表5可知,综合得分前三的小麦分别是新麦26、洛旱22、豫麦49。新麦26面团稳定时间、形成时间、拉伸面积、沉淀指数最高,最大拉伸阻力、50 mm拉伸阻力、千粒重、灰分、硬度指数、蛋白质含量、延伸性较高,而面团稳定时间、形成时间、拉伸面积、沉淀指数、最大拉伸阻力、50 mm拉伸阻力、灰分、硬度指数、蛋白质含量与第1主成分呈正相关,千粒重、延伸性分别与第2、第4主成分呈正相关,所以新麦26 F1第一,F2第四,F4第一,综合评分第一;洛旱22粉质质量指数最高,灰分、沉淀指数、面筋指数、形成时间、面团稳定时间较高,但延伸性较低,粉质质量指数、灰分、面筋指数、形成时间、面团稳定时间为第1主成分正向指标,沉淀指数为第2主成分正向指标,所以洛旱22 F1第三,F2第三,综合评分第二;豫麦49灰分、硬度指数、蛋白质含量、面筋指数、最大拉伸阻力、50 mm拉伸阻力最高,湿面筋含量较高,拉伸面积较低,灰分、硬度指数、蛋白质含量、面筋指数、最大拉伸阻力、50 mm拉伸阻力与第1主成分呈正相关,湿面筋含量与第3主成分呈正相关,其他指标不占优势,所以该品种F1第二,F3第三,综合评分第三。
聚类分析是研究作物品种资源差异和分类的评价方法。对18份不同小麦品种进行聚类分析,基于14个品质性状构建了聚类分析图(图2),对不同类群14个品质参数进行统计分析(表6)。在平方欧式距离为6处,小麦品种可分为三大类:第Ⅰ类包括10个小麦品种,分别为豫农211、周麦22、周麦27、百农307、矮抗58、温麦168、豫农982、平麦189、伟隆169和众麦1号,与其他类群相比,其延伸性表现最好,硬度指数表现适中,其他指标均表现最差,主要特征为籽粒品质居中,面粉品质和面团品质最差,表明该类群磨粉品质较好,加工品质较差;第Ⅱ类包括6个小麦品种,分别为百农4199、洛旱22、郑麦369、周麦30、存麦11和郑麦188,其硬度指数和延伸性表现最差,其他指标均表现适中,主要特征为籽粒品质较差,面粉品质和面团品质居中,表明其磨粉品质较差,加工品质较好;第Ⅲ类包括2个小麦品种,即豫麦49号和新麦26,其粉质质量指数和延伸性表现适中,其他指标均表现最好,主要特征为籽粒品质和面粉品质最好,面团品质较好,表明其磨粉、加工品质及食用品质均较好。
研究表明,小麦面筋蛋白中的醇溶蛋白与面团延伸性有关,是面包、馒头等体积膨胀的主要因素之一,麦谷蛋白吸水后与面团黏弹性有关[36−38]。麦谷蛋白中的高、低分子量麦谷蛋白亚基的数量和性质的变化是小麦面团流变学特性变化的主要原因[39],亚基14+15、17+18、GluB3d等对蛋白质和湿面筋含量具有显著正向效应,亚基17+18、5+10、GluA3f等对面团形成时间和稳定时间具有显著的正向效应[40]。小麦醇溶蛋白中的ω13.5、β63和α72.5等谱带与面筋弹性、膨胀性、黏性及延展性呈正向效应,而ω35.5、γ42.5和β57.5与这些指标呈负向效应[41],因此可通过定向导入与目标性状相关的亚基,或定向突变去除负向效应的亚基,对第Ⅰ类品种的面粉品质和面团品质进行有效改良。第Ⅱ类主要特征为籽粒品质较差,粉质质量指数(153.83 mm)最高,延伸性(132.67 mm)最差,程晓明等[42]协调最大灌浆速率和灌浆持续时间,可以显著提高生理成熟期籽粒质量;蒋欣东[43]通过对化肥减施17%及农药减施30%配施激健,发现小麦籽粒较大且籽粒均匀度较好。第Ⅲ类形成时间(12.40 min)和面团稳定时间(17.20 min)在三个类群中最高,形成时间和稳定时间长的面粉适用于制作馒头面包等食品,且优质面筋可以显著延长稳定时间,提高面团的耐搅拌性能[44]。表明该类群面粉品质含量高,营养品质好。由此得出,类群Ⅰ综合品质表现较差,类群Ⅲ综合品质表现最好,可大致区分小麦品系品质性状综合表现。
本研究测定了河南地区种植的18个不同小麦品种的籽粒、面粉及面团品质特性。试验所测定的15个品质指标均存在差异,其中差异最大指标为形成时间,变异系数为78.96%,容重变异系数为1.89%,差异最小;新麦26的6项指标达到我国小麦品种品质分类标准强筋品质要求,7个品种达到中强筋品质要求。相关性分析和主成分分析将评价指标简化为4个主成分,并对14个指标分别赋予权重,进行综合评价,得到18个小麦品种的综合加工品质从高到低的排序,排名前三依次为新麦26、洛旱22、豫麦49;聚类分析将18个品种归纳为3类,通过综合分析不同类特点,建议在强筋小麦育种改良工作中,可优先考虑类群Ⅲ中强筋小麦新麦26与类群Ⅱ中百农4199、洛旱22等为代表的中强筋小麦作为组合亲本,有效利用品质优良的育成品种对小麦加工品质进行改良及种质资源创新,有针对性地对其开发利用,加工生产专用面粉相关产品。本研究结果为筛选优质小麦品种提供了参考,对实现不同小麦品种籽粒或面粉的最终用途专用化具有重要意义,然而,仍需要后续观察和试验来研究其产量和加工品质稳定性。

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2026年第47卷第15期
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doi: 10.13386/j.issn1002-0306.2025080093
  • 接收时间:2025-08-11
  • 首发时间:2026-10-24
  • 出版时间:2026-08-01
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  • 收稿日期:2025-08-11
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    1郑州市产品质量检验检测中心,河南郑州 450000
    2洛阳市农林科学院,河南洛阳 471000

通讯作者:

弓浩然(1992−),男,硕士,助理工程师,研究方向:粮油检测,E-mail:。
谢婕(1988−),女,硕士,农艺师,研究方向:农产品加工,E-mail:。
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2种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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